This report is prepared within Phase 2 of the project Renewable Energy Resource Mapping for the Republic of Zambia. The project objectives is to deliver high quality solar resource mapping and measurement services for renewable energy development implemented...
Vea más +This report is prepared within Phase 2 of the project Renewable Energy Resource Mapping for the Republic of Zambia. The project objectives is to deliver high quality solar resource mapping and measurement services for renewable energy development implemented by the World Bank in Zambia.This report describes results of 24 plus months of the measuring campaign at six solar meteorological stations, installed in Zambia. The report accompanies delivery of site-specific measurements and model data prepared for six sites, where meteorological measurement campaign has been conducted. These solar meteorological stations were installed and operated by GeoSUN Africa (South Africa) with their partner SGS Zambia, and commissioned by the World Bank over the years 2015 to 2017 under the same activity. The data quality control and further processing and integration to the solar models has been conducted by Solargis (Slovakia) under the same project. The 2-year campaign brought a unique set of solar resource measurements for a region in Africa, and climate zone, that have been mapped insufficiently so far. The data helps specialists to better understand solar resource availability and variability, as both are crucial for development of solar power plants and for their efficient integration into existing energy infrastructure. This campaign also contributes to better understanding of performance and uncertainty of solar measuring sensors in tropical conditions. The knowledge based on the analysis of measured and modelled data in this region improves confidence of engineers, designing solar power plants, and investors and banks, providing the financing. One of key benefits of having these type of measurements is that they can be used for improving the solar and meteorological models. We used data from six meteo sites for adaption of Solargis model to the regional climate, and this results in reduced uncertainty of the model outputs, see the summary table below. This way, the improved model is able to generate more accurate solar and meteorological historical data, which reduces uncertainties in technical and financial evaluation of any solar energy project in Zambia. This report describes technical parameters of the measurement campaign, features of the measured data, adaptation of models, summary statistics for the outputs at six meteorological sites, and relevant uncertainties.
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